Characterizing the mechanical contribution of fiber angular distribution in connective tissue: comparison of two modeling approaches (original) (raw)
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An elliptically symmetric angular Gaussian distribution
We define a distribution on the unit sphere S d−1 called the elliptically symmetric angular Gaussian distribution. This distribution, which to our knowledge has not been studied before, is a subfamily of the angular Gaussian distribution closely analogous to the Kent subfamily of the general Fisher–Bingham distribution. Like the Kent distribution, it has ellipse-like contours, enabling modelling of rotational asymmetry about the mean direction, but it has the additional advantages of being simple and fast to simulate from, and having a density and hence likelihood that is easy and very quick to compute exactly. These advantages are especially beneficial for computationally intensive statistical methods, one example of which is a parametric bootstrap procedure for inference for the directional mean that we describe.
International Journal of Solids and Structures, 2012
Constitutive modeling of biological tissues plays an important role in the understanding of tissue behavior and the development of synthetic materials for medical and bio-inspired applications. A structural continuum model that incorporates principal structural features of the tissue can potentially provide the link between microstructure and the macroscopic mechanical response of biological tissues. For most soft biological tissues, including arterial walls and skin tissue, the main load-carrying constituent is presumed to be the distributed collagen fibers embedded in a base matrix. It is believed that the organization of the collagen fibers gives rise to the anisotropy of the material. In this paper, a semi-structural constitutive model is proposed to account for planar fiber distributions with more than one distributed planar fiber property. Motivated by histology information of the wing membrane of the bat, a statistical treatment is formulated in this paper to capture the overall effect of the distribution of fiber cross-sectional area and the distribution of the number of fibers. This formulation is suitable for general cases when more than one fiber property varies spatially. Furthermore, this model is a two-dimensional specialization within the framework of a three-dimensional theory, which is different the formulation based on a fundamentally two-dimensional theory.
Nonlinear elasticity of biological tissues with statistical fibre orientation
Journal of The Royal Society Interface, 2010
The elastic strain energy potential for nonlinear fibre-reinforced materials is customarily obtained by superposition of the potentials of the matrix and of each family of fibres. Composites with statistically oriented fibres, such as biological tissues, can be seen as being reinforced by a continuous infinity of fibre families, the orientation of which can be represented by means of a probability density function defined on the unit sphere (i.e. the solid angle). In this case, the superposition procedure gives rise to an integral form of the elastic potential such that the deformation features in the integral, which therefore cannot be calculated a priori. As a consequence, an analytical use of this potential is impossible. In this paper, we implemented this integral form of the elastic potential into a numerical procedure that evaluates the potential, the stress and the elasticity tensor at each deformation step. The numerical integration over the unit sphere is performed by means of the method of spherical designs, in which the result of the integral is approximated by a suitable sum over a discrete subset of the unit sphere. As an example of application, we modelled the collagen fibre distribution in articular cartilage, and used it in simulating displacementcontrolled tests: the unconfined compression of a cylindrical sample and the contact problem in the hip joint.
Efficient evaluation of the material response of tissues reinforced by statistically oriented fibres
Zeitschrift für Angewandte Mathematik und Physik, 2016
For several classes of soft biological tissues, modelling complexity is in part due to the arrangement of the collagen fibres. In general, the arrangement of the fibres can be described by defining, at each point in the tissue, the structure tensor (i.e., the tensor product of the unit vector of the local fibre arrangement by itself) and a probability distribution of orientation. In this approach, assuming that the fibres do not interact with each other, the overall contribution of the collagen fibres to a given mechanical property of the tissue can be estimated by means of an averaging integral of the constitutive function describing the mechanical property at study over the set of all possible directions in space. Except for the particular case of fibre constitutive functions that are polynomial in the transversely isotropic invariants of the deformation, the averaging integral cannot be evaluated directly, in a single calculation because, in general, the integrand depends both on deformation and on fibre orientation in a non-separable way. The problem is thus, in a sense, analogous to that of solving the integral of a function of two variables, which cannot be split up into the product of two functions, each depending only on one of the variables. Although numerical schemes can be used to evaluate the integral at each deformation increment, this is computationally expensive. With the purpose of containing computational costs, this work proposes approximation methods that are based on the direct integrability of polynomial functions and that do not require the step-by-step evaluation of the averaging integrals. Three different methods are proposed: a) a Taylor expansion of the fibre constitutive function in the transversely isotropic invariants of the deformation; b) a Taylor expansion of the fibre constitutive function in the structure tensor; c) for the case of a fibre constitutive function having a polynomial argument, an approximation in which the directional average of the constitutive function is replaced by the constitutive function evaluated at the directional average of the argument. Each of the proposed methods approximates the averaged constitutive function in such a way that it is multiplicatively decomposed into the product of a function of the deformation only and a function of the structure tensors only. In order to assess the accuracy of these methods, we evaluate the constitutive functions of the elastic potential and the Cauchy stress, for a biaxial test, under different conditions, i.e., different fibre distributions and different ratios of the nominal strains in the two directions. The results are then compared against those obtained for an averaging method available in the literature, as well as against the integration made at each increment of deformation.
Journal of Biomechanical Engineering, 2004
Accurate constitutive models are required to gain further insight into the mechanical behavior of cardiovascular tissues. In this study, a structural constitutive framework for cardiovascular tissues is introduced that accounts for the angular distribution of collagen fibers. To demonstrate its capabilities, the model is applied to study the biaxial behavior of the arterial wall and the aortic valve. The pressure–radius relationships of the arterial wall accurately describe experimentally observed sigma-shaped curves. In addition, the nonlinear and anisotropic mechanical properties of the aortic valve can be analyzed with the proposed model. We expect that the current model offers strong possibilities to further investigate the complex mechanical behavior of cardiovascular tissues, including their response to mechanical stimuli.
Gaussian Distribution and their Application : Muscle Fiber Distribution on Cross-Section Muscle Area
2008
From a distribution of people’s heights in a group to error signal detection, the Gaussian Distribution provides various applications to predict the probability of a generalized distribution. Especially, the Gaussian Distribution is generally applicable to explain a biological or physiological phenomenon because it shows the most realistic distribution in biology and physiology. In the human muscle, there are hundreds of muscle fibers to compose each muscle part. Depending on the location of each muscle fiber, it generates a different action potential to compose of the Electromyogram (EMG). Because of this fact, the locations of different muscle fibers are important. It will be shown how the location of each muscle fiber, based on the Gaussian Distribution, affects the final calculated muscle fiber action potential in this paper.
Zeitschrift fuer angewandte mathematik und physik, 2016
The distribution of collagen fibers across articular cartilage layers is statistical in nature. Based on the concepts proposed in previous models, we developed a methodology to include the statistically distributed fibers across the cartilage thickness in the commercial FE software COMSOL which avoids extensive routine programming. The model includes many properties that are observed in real cartilage: finite hyperelastic deformation, depth-dependent collagen fiber concentration, depth- and deformation-dependent permeability, and statistically distributed collagen fiber orientation distribution across the cartilage thickness. Numerical tests were performed using confined and unconfined compressions. The model predictions on the depth-dependent strain distributions across the cartilage layer are consistent with the experimental data in the literature.
International Journal of Engineering Science, 2014
Gradual fiber recruitment is one of the stiffening mechanisms observed in collagen reinforced biological tissues. Given the natural statistical distribution of the fiber orientation in biological materials, in agreement with experimental findings it is reasonable to assume a stochastic nature of the fiber recruitment mechanism. In the present study, we consider the presence of a stochastic recruitment mechanism in a hyperelastic fiber reinforced material model characterized by statistical distributions of the fiber orientation. The material model is based on a second order approximation of the strain energy density, considered as a function of the fourth pseudo-invariant I 4 , and on the multiplicative decomposition of the deformation gradient and, consequently, of the stretch. For a planar distribution of the fiber orientation, we choose an exponential analytical expression of the strain energy density and derive the stress and stiffness tensors. The mechanical behavior of the model is assessed, through uniaxial tests, by distinguishing the mean and the variance contributions of I 4 to the model is validated against experimental data.
Mechanics Research Communications, 2010
Constitutive models for arterial tissue have been an active research field during the last years. The main micro-constituents of blood vessels are different types of cells and the extra-cellular matrix formed by an isotropic high water content ground substance and a network composed of elastin and collagen fibres. Usually the arterial tissue has been modelled as a hyperelastic material within the framework of continuum mechanics, whereas inclusion of structural tensors into constitutive laws is the most widely used technique to introduce the anisotropy induced by the fibres. Though the different existing fibre bundles present a clear preferential direction, the dispersion inherent to biological tissue advices using of constitutive models including representative structural information associated to the spatial probabilistic distribution of the fibres. Lately, microsphere-based models have demonstrated to be a powerful tool to incorporate this information. The fibre dispersion is incorporated by means of an Orientation Density Function (ODF) that weights the contribution of each fibre in each direction of the micro-sphere. In previous works the rotationally symmetric von Mises ODF was successfully applied to the modelling of blood vessels. In this study, the inclusion of the Bingham ODF into microsphere-based model is analysed. This ODF exhibits some advantages with respect to the von Mises one, like a greater versatility and a comparable response to simple tension and equibiaxial tension tests.